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ljfwhy

新虫 (初入文坛)

[求助] 请大家帮帮我,会议检索情况,急用,先谢谢

我需要检索页面的截图,谢谢大家
发我邮箱ljfwhy@gmail.com,或者直接贴图,谢谢!
一篇:News Recommendation in Forum-Based Social Media
另一篇:A Dynamic Wireless Spectrum Allocation Algorithmfor Sliding Scheduled Demands

急用,如果上午十点之前弄好就万分感激了
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ljfwhy

新虫 (初入文坛)

imyourkobe: 不要自己回复帖子,可以在原帖编辑。 2011-12-09 10:13:12
PS:AAAI是国际顶级,请再帮我看看是否SCI检索。谢谢。
2楼2011-12-09 07:40:02
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学术还是艺术

木虫 (职业作家)

大木虫创始人

【答案】应助回帖


imyourkobe(金币+1): 谢谢应助。 2011-12-09 10:13:28
引用回帖:
1楼: Originally posted by ljfwhy at 2011-12-09 07:35:14:
我需要检索页面的截图,谢谢大家
发我邮箱ljfwhy@gmail.com,或者直接贴图,谢谢!
一篇:News Recommendation in Forum-Based Social Media
另一篇:A Dynamic Wireless Spectrum Allocation  ...

第一篇:


拿破仑说过:没有签名档的水兵不是好水兵。有签名空间就不能浪费,伟大领袖毛主席说过:贪污和浪费是最大的犯罪。我是真的不想犯罪。。。
3楼2011-12-09 08:40:43
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学术还是艺术

木虫 (职业作家)

大木虫创始人

【答案】应助回帖

引用回帖:
1楼: Originally posted by ljfwhy at 2011-12-09 07:35:14:
我需要检索页面的截图,谢谢大家
发我邮箱ljfwhy@gmail.com,或者直接贴图,谢谢!
一篇:News Recommendation in Forum-Based Social Media
另一篇:A Dynamic Wireless Spectrum Allocation  ...

第二篇:


拿破仑说过:没有签名档的水兵不是好水兵。有签名空间就不能浪费,伟大领袖毛主席说过:贪污和浪费是最大的犯罪。我是真的不想犯罪。。。
4楼2011-12-09 08:43:53
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学术还是艺术

木虫 (职业作家)

大木虫创始人

引用回帖:
2楼: Originally posted by ljfwhy at 2011-12-09 07:40:02:
PS:AAAI是国际顶级,请再帮我看看是否SCI检索。谢谢。

SCI不会查。。
拿破仑说过:没有签名档的水兵不是好水兵。有签名空间就不能浪费,伟大领袖毛主席说过:贪污和浪费是最大的犯罪。我是真的不想犯罪。。。
5楼2011-12-09 08:49:42
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imyourkobe

铁杆木虫 (著名写手)

【答案】应助回帖

1. User comments for news recommendation in forum-based social media  
作者: Li, Q (Li, Qing); Wang, J (Wang, Jia); Chen, YP (Chen, Yuanzhu Peter)1; Lin, ZX (Lin, Zhangxi)2  
来源出版物: INFORMATION SCIENCES  卷: 180   期: 24   页: 4929-4939   DOI: 10.1016/j.ins.2010.08.044   出版年: DEC 15 2010  
被引频次: 1 (来自 Web of Science)  
引用的参考文献: 33 [ 查看 Related Records ]     引证关系图      
摘要: News recommendation and user interaction are important features in many Web-based news services. The former helps users identify the most relevant news for further information. The latter enables collaborated information sharing among users with their comments following news postings. This research is intended to marry these two features together for an adaptive recommender system that utilizes reader comments to refine the recommendation of news in accordance with the evolving topic. This then turns the traditional "pushdata" type of news recommendation to "discussion" moderator that can intelligently assist online forums. In addition, to alleviate the problem of recommending essentially identical articles, the relationship (duplicate, generalization, or specialization) between recommended news articles and the original posting is investigated. Our experiments indicate that our proposed solutions provide an improved news recommendation service in forum-based social media. (C) 2010 Elsevier Inc. All rights reserved.  
文献类型: Article  
语种: English  
作者关键词: News recommendation; Recommender system; Content-based filtering; Collaborative filtering; Social media; User comment; Information retrieval  
地址:
1. Mem Univ Newfoundland, St John, NF A1C 5S7, Canada
2. Texas Tech Univ, Lubbock, TX 79409 USA  
电子邮件地址: kooliqing@gmail.com  
基金资助致谢:
基金资助机构 授权号
Scientific Research Starting Foundation for Returned Overseas Chinese Scholars   
National Natural Science Foundation of China (NSFC)  60803106  
Fok Ying-Tong Education Foundation, China  121068  
Natural Sciences and Engineering Research Council (NSERC) of Canada  303958-2010  

[显示基金资助信息][隐藏基金资助信息]   

This work has been supported by the Scientific Research Starting Foundation for Returned Overseas Chinese Scholars, the National Natural Science Foundation of China (NSFC) (Grant No. 60803106), the Fok Ying-Tong Education Foundation, China (Grant No. 121068), and the Discovery Grants of Natural Sciences and Engineering Research Council (NSERC) of Canada (No. 303958-2010).

出版商: ELSEVIER SCIENCE INC, 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA  
Web of Science 分类: Computer Science, Information Systems  
学科类别: Computer Science  
IDS 号: 677DA  
ISSN: 0020-0255

2.没有SCI检索信息。

[ Last edited by imyourkobe on 2011-12-9 at 10:12 ]
6楼2011-12-09 10:10:17
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